The data analysis interview asks you how you would predict some number. First you go through data ideation (if you could gather any reasonable data, what would you want?), then you talk about how you would go about engineering features and cleaning your data, then you talk about what kind of model you would use and why. They really drill into your answers, and you are likely not going to pass if you don't have a lot of experience in predictive modeling. Watch the mock interview video on their website for an easy example of what this is like.
Quantitative Research Intern Interview Questions
3,500 quantitative research intern interview questions shared by candidates
Two points are uniformly distributed around the circumference of a unit circle. What is the expected value of the distance between them?
Q: given an array of 2d points and an x-input query, return the corresponding y using linear interpolations.
Citibike questions run through potentially how you would do somehting
Linear regression questions and probability, some time series stuff
. Asked about research in my current role, digging into details about diffusion models I worked on (and he clearly did not know any basics and seemed he did not want to admit that). Quite unpleasant. Then technical question about parameter estimation from noisy observations of Gaussian random variables.
Asking me to accept I'm wrong every 5 minutes.
Simple coding and data analysis
Derive the closed form solution for a cost function
Predict rental housing price in city
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